Apparatus and methods for collecting global data during a reticle inspection

ABSTRACT

Disclosed is a method of inspecting a reticle defining a circuit layer pattern that is used within a corresponding semiconductor process to generate corresponding patterns on a semiconductor wafer. A test image of the reticle is provided, and the test image has a plurality of test characteristic values. A baseline image containing an expected pattern of the test image is also provided. The baseline image has a plurality of baseline characteristic values that correspond to the test characteristic values. The test characteristic values are compared to the baseline characteristic values such that a plurality of difference values are calculated for each pair of test and baseline characteristic values. Statistical information is also collected.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Pat. No. 09/304,437,(Attorney Docket No. KLA1P006) filed May 3, 1999, now U.S. Pat.6,516,085 by James N. Wiley, Jun Ye, Shauh-The Juang, David S. Alles,Yen-Wen Lu, and Yu Cao and entitled “APPARATUS AND METHODS FORCOLLECTING GLOBAL DATA DURING A RETICLE INSPECTION.” That application isincorporated herein by reference in its entirety and for all purposes.

BACKGROUND OF THE INVENTION

The present invention relates generally to integrated circuit design andfabrication systems. More specifically, the invention relates tomechanisms for inspecting reticles.

Generation of reticles and subsequent optical inspection of suchreticles have become standard steps in the production of semiconductors.Initially, circuit designers provide circuit pattern data, whichdescribes a particular integrated circuit (IC) design, to a reticleproduction system, or reticle writer. The circuit pattern data istypically in the form of a representational layout of the physicallayers of the fabricated IC device. The representational layouttypically includes a representational layer for each physical layer ofthe IC device (e.g., gate oxide, polysilicon, metallization, etc.),wherein each representational layer is composed of a plurality ofpolygons that define a layer's patterning of the particular IC device.

The reticle writer uses the circuit pattern data to write (e.g.,typically, an electron beam writer or laser scanner is used to expose areticle pattern) a plurality of reticles that will later be used tofabricate the particular IC design. A reticle inspection system may theninspect the reticle for defects that may have occurred during theproduction of the reticles.

A reticle or photomask is an optical element containing at leasttransparent and opaque regions, and sometimes semi-transparent and phaseshifting regions, as well, which together define the pattern of coplanarfeatures in an electronic device such as an integrated circuit. Reticlesare used during photolithography to define specified regions of asemiconductor wafer for etching, ion implantation, or other fabricationprocess. For many modern integrated circuit designs, an opticalreticle's features are between about 1 and about 5 times larger than thecorresponding features on the wafer. For other exposure systems (e.g.,x-ray, e-beam, and extreme ultraviolet) a similar range of reductionratios also apply.

Optical reticles are typically made from a transparent medium such as aborosilicate glass or quartz plate on which is deposited an opaqueand/or semi-opaque layer of chromium or other suitable material.However, other mask technologies are employed for direct e-beam exposure(e.g., stencil masks), x-ray exposure (e.g., absorber masks), etc. Thereticle pattern may be created by a laser or an e-beam direct writetechnique, for example, both of which are widely used in the art.

After fabrication of each reticle or group of reticles, each reticle istypically inspected by illuminating it with light emanating from acontrolled illuminator. A test image of a portion of the reticle isconstructed based on the portion of the light reflected, transmitted, orotherwise directed to a light sensor. Such inspection techniques andapparatus are well known in the art and are embodied in variouscommercial products such as many of those available from KLA-TencorCorporation of San Jose, Calif.

During a conventional inspection process, the test image of the reticleis typically compared to a baseline image. Typically, the baseline imageis either generated from the circuit pattern data or from an adjacentdie on the reticle itself. Either way, the test image features areanalyzed and compared with corresponding features of the baseline image.That is, an edge position within the test image is subtracted from acorresponding edge position within the baseline image to calculate adifference value. Each difference value is then compared with apredetermined threshold value. If the test image feature varies from thebaseline feature by more than the predetermined threshold, a defect isdefined and an error is reported.

An error report for a particular test image will typically only includea list of errors that were detected within the particular test image andcorresponding reticle (e.g., the location of each error and a smallimage of that defect). In other words, the list represents the featureswithin the test image that varied from the baseline image by more thanthe predetermined threshold. Specifically, the list represents the edgepositions within the test image that varied more than the predeterminedthreshold from the corresponding edge positions of the baseline image,as well as any extra or missing features.

Although conventional inspection techniques provide adequate error datain some applications, this data proves limiting under certainconditions. For example, a user of the reticle may wish to know theactual measured values of particular characteristics of features (i.e.,edge position) within the test image as a function of position on thereticle. Additionally, the user may wish to know other measurable valuesof other characteristics (e.g., line width and corner rounding values).By way of another example, the user may wish to know the amount ofvariance between the features of the test image and the features of thebaseline image as a function of position on the reticle.

Although these variance values may not be large enough to be defined aserrors, they may be useful in process control and/or monitoring.Additionally, statistical information of measurable characteristics as afunction of position on the reticle, for example, may be used toincrease the sensitivity of the inspection process itself, among otherapplications. That is, the threshold may be adjusted for certain areasof the reticle that typically have more errors than other areas of thereticle. Unfortunately, conventional inspection apparatus and techniquesmerely provide a list of errors present on the reticle and do notprovide any statistical information of measured characteristics of thereticle.

Thus, inspection apparatus and techniques for improving and enhancinginformation that is output from the inspection procedure are needed.More specifically, inspection mechanisms for providing statisticalinformation about measured characteristics of the reticle are needed.

SUMMARY OF THE INVENTION

Accordingly, the present invention addresses the above problems byproviding apparatus and methods for providing statistical informationduring the inspection process. As each feature or region of a test imageof a portion of a reticle is evaluated, statistical information iscollected for the entire test image. That is, as features of the testimage are compared to features of the baseline image, measuredcharacteristic values of the test image (or difference values betweenthe test and baseline images) are collected. The collected measured ordifference values may be correlated to a number of reticle parameters,such as a reticle position, a particular area on the reticle, a featuredensity value of a particular area of the reticle, or a processassociated with the reticle under test. A count of the measuredcharacteristic or difference values may also be collected. Thiscollected data (e.g., the count and measured values or differencevalues) may then be used to compute other statistical parameters, suchas standard deviation, minimum, maximum, range (maximum minus minimum),and median or average values.

In one embodiment, a method of inspecting a reticle defining a circuitlayer pattern that is used within a corresponding semiconductor processto generate corresponding patterns on a semiconductor wafer isdisclosed. A test image of the reticle is provided, and the test imagehas a plurality of test characteristic values. A baseline imagecontaining an expected pattern of the test image is also provided. Thebaseline image has a plurality of baseline characteristic values thatcorrespond to the test characteristic values. The test characteristicvalues are compared to the baseline characteristic values such that aplurality of difference values are calculated for each pair of test andbaseline characteristic values. Statistical information is alsocollected.

In a specific embodiment, the statistical information includes a secondplurality of test characteristics values that are of a different type ofcharacteristic than the first plurality of test characteristic valuesthat are compared to the baseline characteristic values. The statisticalinformation may also include a standard deviation value of the secondtest characteristic values, a median value of the second testcharacteristic values, and/or an average value of the second testcharacteristic values. The first test characteristic values may be inthe form of edge position values and the second test characteristicvalues include line width values, corner rounding values, transmissionvalues, gate line width values, contact area values, and/or misalignmentvalues.

In another embodiment, a method of monitoring or adjusting a reticleprocess that is used to generate reticles is disclosed. The methodincludes (a) generating a first reticle using a reticle process; (b)providing a test image of the first reticle, wherein the test image hasa plurality of test characteristic values; (c) providing a baselineimage containing an expected pattern of the test image, wherein thebaseline image has a plurality of baseline characteristic values thatcorrespond to a first subgroup of the test characteristic values; (d)comparing the first subgroup of test characteristic values to thecorresponding baseline characteristic values such that a plurality ofdifference values are calculated for each pair of test and baselinecharacteristic values; (e) collecting statistical information based on asecond subgroup of the test characteristic values of the first reticle;and (f) adjusting a process parameter of the reticle process if thestatistical information indicates that the second subgroup of testcharacteristic values deviate from the baseline values by more than apredetermined amount.

In one aspect, the first subgroup is equal to the second subgroup oftest characteristic values. In yet another embodiment, the aboveoperations (a) through (e) are repeated for a second reticle. Thestatistical information for the second reticle is compared to thestatistical information for the first reticle, and a process parameterof the reticle process is adjusted if the statistical information forthe second reticle varies from the statistical information for the firstreticle by more than a second predetermined amount. In yet anotherembodiment, the process parameter of the reticle process is adjusted soas to reduce variations in the second subgroup of test characteristicvalues as a function of reticle position.

In another method aspect, a semiconductor process is monitored oradjusted. A reticle defining a circuit layer pattern and statisticalinformation about selected characteristic values of the circuit layerpattern are provided. A circuit layer on a semiconductor wafer isgenerated using the reticle in a photolithography process. The resultingcircuit layer is inspected based at least in part on the statisticalinformation.

In yet another aspect, a computer readable medium containing programinstructions for inspecting a reticle defining a circuit layer patternthat is used within a corresponding semiconductor process to generatecorresponding patterns on a semiconductor wafer is also disclosed. Thecomputer readable medium includes computer readable code for (i)providing a test image of the reticle, wherein the test image having aplurality of test characteristic values, (ii) providing a baseline imagecontaining an expected pattern of the test image, wherein the baselineimage having a plurality of baseline characteristic values thatcorrespond to the test characteristic values, (iii) comparing the testcharacteristic values to the baseline characteristic values such that aplurality of difference values are calculated for each pair of test andbaseline characteristic values, (iv) collecting statistical information,and a computer readable medium for storing the computer readable codes.

In yet another embodiment, a computer readable medium containing programinstructions for monitoring or adjusting a semiconductor process isdisclosed. The computer readable medium includes computer readable codefor providing a reticle defining a circuit layer pattern, computerreadable code for providing statistical information about selectedcharacteristic values of the circuit layer pattern, computer readablecode for generating a circuit layer on a semiconductor wafer using thereticle in a photolithography process, computer readable code forinspecting the resulting circuit layer based at least in part on thestatistical information, and a computer readable medium for storing thecomputer readable codes.

In another embodiment, a computer readable medium containing programinstructions for monitoring or adjusting a reticle process is alsodisclosed. The computer readable medium includes computer code for (a)generating a first reticle using a reticle process, (b) providing a testimage of the first reticle, wherein the test image has a plurality oftest characteristic values, (c) providing a baseline image containing anexpected pattern of the test image, wherein the baseline image has aplurality of baseline characteristic values that correspond to the testcharacteristic values, (d) comparing the test characteristic values tothe baseline characteristic values such that a plurality of differencevalues are calculated for each pair of test and baseline characteristicvalues, (e) collecting statistical information based on the plurality oftest characteristic values of the first reticle, and (f) adjusting aprocess parameter of the reticle process if the statistical informationindicates that the test characteristic values deviate from the baselinecharacteristic values by more than a predetermined amount.

These and other features and advantages of the present invention will bepresented in more detail in the following specification of the inventionand the accompanying figures which illustrate by way of example theprinciples of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be readily understood by the followingdetailed description in conjunction with the accompanying drawings,wherein like reference numerals designate like structural elements, andin which:

FIG. 1 is a flowchart illustrating an integrated circuit design processin accordance with one embodiment of the present invention.

FIG. 2 is a flowchart illustrating the operation of FIG. 1 of inspectingand evaluating the fabricated reticle in accordance with one embodimentof the present invention.

FIG. 3 is a flowchart illustrating the operation of FIG. 2 of comparingthe test and baseline images in accordance with one embodiment of thepresent invention.

FIG. 4 is a diagrammatic representation of line width characteristics ofa test image and corresponding baseline image in accordance with oneembodiment of the present invention.

FIG. 5 is a diagrammatic representation of corner roundingcharacteristics of a test image and corresponding baseline image inaccordance with one embodiment of the present invention.

FIGS. 6A and 6B are diagrammatic representations of contact areacharacteristics of a test image and corresponding baseline image inaccordance with one embodiment of the present invention.

FIG. 7 is a diagrammatic representation of alignment characteristics ofa test image and corresponding baseline image in accordance with oneembodiment of the present invention.

FIG. 8 shows a reticle inspection system upon which the process of FIG.1 of evaluating the reticle is implemented in one embodiment of thepresent invention.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

Reference will now be made in detail to the specific embodiments of theinvention. Examples of these specific embodiments are illustrated in theaccompanying drawings. While the invention will be described inconjunction with these specific embodiments, it will be understood thatit is not intended to limit the invention to the described embodiments.On the contrary, it is intended to cover alternatives, modifications,and equivalents as may be included within the spirit and scope of theinvention as defined by the appended claims. In the followingdescription, numerous specific details are set forth in order to providea thorough understanding of the present invention. The present inventionmay be practiced without some or all of these specific details. In otherinstances, well known process operations have not been described indetail in order not to unnecessarily obscure the present invention.

FIG. 1 is a flowchart illustrating an integrated circuit design process100 in accordance with one embodiment of the present invention.Initially, in operation 102, an integrated circuit (IC) device isdesigned using any suitable design techniques. For example, an ICdesigner may use preexisting schematic library blocks to form the ICdevice using, for example, electronic design automation (EDA) tools. Insome cases, the IC designer may create the IC device or part of the ICdevice from scratch with the aid of any suitable design system, such asconventional computer aided design (CAD) tools. For example, the ICdesigner may use a schematic CAD tool to plan the logic diagrams for aparticular IC device. Still further, the IC designer may write adescription of the IC device or portions of the IC device with the aidof a hardware design language, such as VHDL.

Next, in operation 104 the IC designer generates a circuit patterndatabase (commonly referred to as a “layout”) from the IC design inoperation 104. The circuit pattern database is composed of a pluralityof electronic representations of layout patterns for IC layers that arelater converted into a plurality of reticles that are used to fabricatea plurality of physical layers of an IC device. Each physical layer ofthe fabricated IC device corresponds to one of the reticles and anassociated one of the electronic representations of the circuit patterndatabase. For example, one electronic representation may correspond to adiffusion pattern on a silicon substrate, another to a gate oxidepattern, another to a gate polysilicon pattern, another to a contactpattern on an interlayer dielectric, another to a line pattern on ametallization layer, and so on. Each electronic representation iscomposed of a plurality of polygons or other shapes (herein, referred toas “figures”), which together define the reticle pattern.

The circuit pattern database may be generated using any suitabletechnique, for example, by using EDA or CAD tools. For example, the ICdesigner may manually lay out the circuit patterns for the IC devicewith or without preexisting library cells. Alternatively, a synthesistool may automatically create circuit patterns for the IC device fromscratch or by piecing together preexisting library cells.

After the circuit pattern database is generated, the circuit patterndatabase is used to produce a plurality of reticles in operation 106.The reticles may be produced by any suitable pattern generator orreticle writer equipment, such as a MEBES” 4500, commercially availablefrom ETEC of Hayward, Calif.

Each reticle corresponds to one or more electronic representation(s)from the circuit pattern database. A reticle is then inspected inoperation 108, and it is determined whether the reticle passesinspection in operation 110. If the reticle passes inspection, thereticle may then be used to fabricate a physical layer of the IC devicein operation 112. However, if the reticle does not pass inspection, thereticle is either repaired or remade in operation 114, and the newreticle is inspected in operation 108. Operations 106 through 112 may beimplemented for some or all of the electronic representations of thecircuit pattern database.

The present invention may be implemented on any suitable inspectiontools. For example, a KLA 301, 351, or 353UV Reticle Inspection Tool,commercially available from KLA-Tencor of San Jose, Calif., may beemployed. One embodiment of an inspection system is described below inreference to FIG. 8.

FIG. 2 is a flowchart illustrating the operation 108 of FIG. 1 ofevaluating the fabricated reticle in accordance with one embodiment ofthe present invention. Initially, in operation 601 a baseline image ofthe reticle may be generated or “rendered” from the provided circuitpattern database. The baseline image may be generated in any suitablemanner, such as by merely directly converting the contents of thecircuit pattern database into an image. Alternatively, the circuitpattern database may be rendered by simulating fabrication results frommaking a reticle that perfectly matches the circuit pattern database.For example, the corners of a circuit pattern in the baseline image maybe rounded to account for corner rounding that commonly occurs duringfabrication of a reticle.

The baseline image may also include simulated optical effects fromretrieving an optical image of the simulated reticle. Such opticaleffects are necessarily encountered when an optical inspection techniqueis used to evaluate a reticle.

Alternatively, the baseline image may be generated from an adjacent dieof the reticle in a die-to-die inspection approach. In this approach,the images of two supposedly identical patterns on a reticle aregenerated, one for a baseline image and one for a test image describedbelow. Note that many reticles contain the layout patterns of multipleidentical (and adjacent) die.

After the baseline image has been provided at operation 601, the reticleis inspected to obtain a test image of the reticle or a portion of thereticle under analysis in operation 604. Any suitable mechanism may beimplemented for obtaining the test image. For example, an optical orebeam image be obtained.

In operation 606, the test image is compared to the baseline image. Thecomparison may include any suitable techniques for analyzing thereticle. As described above, a measured characteristic value of the testimage may be compared to a corresponding characteristic value of thebaseline image. For example, a line width value of the test image may becompared to a line width value of the baseline image. Severalembodiments of comparison techniques are described in U.S. patentapplication Ser. No. 09/213,744, entitled “Mechanisms for Making andInspecting Reticles” by Glasser, et al., filed on Dec. 17, 1998, whichis herein incorporated by reference in its entirety.

FIG. 3 is a flowchart illustrating the operation 606 of FIG. 2 ofcomparing the baseline and test images in accordance with one embodimentof the present invention. Generally, the test image may be divided intoa plurality of regions (herein referred to as “patches”) that areanalyzed separately during the inspection process. Each patch may be anysuitable size for efficiently analyzing the test image. For example,processing resources may be limited and require a relatively small patchsize. In one embodiment, the patch is about 100 by 25 μm.

Initially, a first test patch is obtained from the test image inoperation 302. A corresponding baseline patch is also obtained from thebaseline image in operation 304. In other words, the baseline image mayalso be divided into a plurality of patches such that each baselinepatch may be compared to each test patch. In operation 306, a pair offeatures are obtained from the test and baseline patches. That is, afeature is obtained from the test patch, and a corresponding feature isobtained from the baseline patch.

One or more characteristics of the feature from the test and baselinepatches are then compared in operation 308. The characteristics may beany measurable characteristic that is suitable for analyzing the sample.Some examples of measurable characteristics are line width, cornerrounding, transmission, gate-line width, contact area, and alignmentcharacteristics. Several embodiments of techniques for comparingdifferent characteristics are further described in reference to FIGS. 4through 7.

Statistical information is then collected and/or generated based oncomparison results in operation 310. For example, as features areanalyzed and compared, measured values of particular characteristics ofthe test image (e.g., line width or corner rounding measurements) may becollected. The statistical information may also include differencevalues between the characteristic values of the test image and thebaseline image. A standard deviation, median, average, maximum, minimum,and/or range (maximum minus minimum) value of a particularcharacteristic's measured or difference values may also be calculatedand stored in operation 310.

Statistical information may be collected as a function of position onthe reticle, as well as a function of any other suitable parameter. Forexample, measured or difference values for a given characteristic (e.g.,line width) may be collected and correlated with feature density ofparticular areas of the reticle. That is, measured or difference valuesmay be correlated with different regions of the patch or reticle thathave different density values. By way of another example, statisticalinformation may be collected as a function of a process type thatcorresponds to the reticle under test. In other words, statisticalinformation for a particular characteristic is recorded for severalreticles as a function of reticle type.

Likewise, other statistical information may be calculated as a functionof any suitable reticle parameter. For example, average, median,maximum, minimum, range, and/or standard deviation values may becalculated as a function of reticle region, feature density value,and/or a process associated with the reticle. By way of specificexample, a single average characteristic or difference value may becalculated for an entire reticle. Thus, average characteristic valuesmay be compared between different reticles and/or associated processes.

Alternatively, an average characteristic or difference value may becalculated for particular regions of the reticle. These average valuesmay then be correlated to other reticle parameters associated with theparticular regions of the reticle, such as feature density or regionorientation (e.g., a region that is positioned within the outer part ofthe reticle versus a region that is positioned within the innerportion).

This information may be calculated on the fly as the characteristicvalues are compared, or calculated after all comparisons are complete.In the later embodiment, a count is retained of the number ofcharacteristic or difference values such that certain statisticalinformation may be calculated, such as average, median, maximum,minimum, range, and/or deviation values.

After statistical information is collected, it may be then be determinedwhether there is an error in operation 312. In other words, it isdetermined whether the test feature's measured characteristic variesfrom the baseline feature's corresponding characteristic by more then apredetermined threshold. If an error is present, the error may bereported in operation 316. If there is no error present, it is thendetermined whether there are more features to analyze within the currentpatch in operation 314.

If there are more features, a next pair of features are obtained inoperation 306, and compared in operation 308. Operation 306 and 308 arerepeated for the remaining features within the current patch. If it isdetermined that there are not more features to analyze within thecurrent patch, it is then determined whether there are more patches toanalyze within the test image in operation 318. If there are morepatches to analyze, the entire process 606 is repeated. If there are nomore patches to process, the process ends.

As mentioned above, several different measured characteristics may beincluded within the analysis of the reticle. Each measuredcharacteristic of the test image may be compared to a correspondingcharacteristic of the baseline image. These comparisons may result in anerror being reported. As characteristics are compared, statisticalinformation may be compiled regarding the measured characteristics. Thestatistical information may include characteristics that were compared,as well as characteristics that were not compared. That is, statisticalinformation may be generated for any number and type of measurablecharacteristics.

FIG. 4 is a diagrammatic representation of line width characteristics ofa test image and corresponding baseline image in accordance with oneembodiment of the present invention. As shown, a line width 402 of afeature within the test image is compared to a corresponding line width404 of the base line image. If the differences between the line widthvalue (represented by 406 a and 406 b) are greater then a predeterminedthreshold value, an error may be defined and reported.

Whether or not the line width values are compared and/or an error isreported, statistical information about the line width values may becollected and/or generated. For example, the actual line width value 402of the test image may be stored. Additionally, the difference values 406a and 406 b between the line width of the test image and baseline imagemay be stored. Additionally or alternatively, an average line widthvalue, a median line width value, a maximum line width value, a minimumline width value, a range line width value (maximum minus minimum),and/or a standard deviation value may be calculated as multiple linewidths are analyzed or after all line widths are analyzed.

FIG. 5 is a diagrammatic representation of corner roundingcharacteristics of a test image and corresponding baseline image inaccordance with one embodiment of the present invention. As shown, acorner 504 of the test image has a number of associated radii 510.Likewise, a corner 502 of the corresponding baseline image has a numberof associated radii 508.

Each of the radii 510 of the test image may be compared to an associatedradii 508 of the baseline image. For example, radii 408A of the baselineimage may be compared to radii 510 a of the test image. If the testimage radii varies from the corresponding baseline radii by more than apredetermined threshold, an error may be flagged. As in a line widthanalysis, the actual radii values of the test image and/or computeddifferences between the radii of the test and baseline images may bestored. Additionally or alternatively, other statistical information maybe generated and stored. For example, a standard deviation, average,maximum, minimum, range, and/or median value may be calculated andstored for the various radii or difference values as a function ofposition on the reticle.

By way of another example, a transmission percentage value may beanalyzed for a given portion of the test image and correspondingreticle. The transmission percentage value represents the amount oflight that is able to penetrate a portion of the reticle. For example, azero percent transmission value indicates that no light may pass throughthe reticle portion, while a 100 percent value indicates that all lightmay pass through the reticle portion. A percentage value that is betweenzero and 100 indicates that some light is blocked in the reticleportion.

The transmission value may be useful for determining whether the reticlehave a stain or water mark on a portion of the reticle that normally hasa 100 percent transmission value. Additionally, the transmissionpercentages of particular areas of the reticle (e.g., areas that areexpected to have 100 percent transmission) may be combined intostatistical information. For example, an average transmission value maybe determined, along with standard deviation values.

Another characteristic of the test image that may be analyzed is contactarea size. The amount of energy throughput for a given contact dependsat least, in part, on the contact area size. Thus, one may wish todetermine whether contacts as represented within the test image have atleast a minimum area size.

FIGS. 6A and 6B are diagrammatic representations of contact areacharacteristics of a test image and corresponding baseline image inaccordance with one embodiment of the present invention. As shown inFIG. 6A, a test contact 856 has a relatively smaller sized area than abaseline contact 852. In contrast, as shown in FIG. 6B, a test contact860 has a same area size as a corresponding baseline contact 858.

If the difference in contact areas between the test contact and baselinecontact is more than a predetermined threshold, an error may be reported(e.g., an error may be reported for the contacts of FIG. 6A, but notFIG. 6B). Additionally, the actual contact area dimensions and/ordifference values may be collected, even when an error is not reported.The stored contact area dimensions and/or difference values may then becombined with other contact area dimensions and/or difference values togenerate meaningful statistical data for the reticle under test. Forexample, mean and/or standard deviation values may be calculated forcontact area sizes on a particular reticle or differences in contactarea sizes of the test and baseline images.

Another characteristic that may be analyzed and collected during theinspection process is alignment or misalignment measurements between afirst group of features and a second group of features. That is, duringreticle generation, groups of features may be misaligned with othergroups of features on the reticle.

FIG. 7 is a diagrammatic representation of misalignment characteristicsof a test image and corresponding baseline image in accordance with oneembodiment of the present invention. A reticle under test 802 includes aplurality of fine patterns (e.g., in columns 806 and rows 804) that areused to fabricate a particular layer of a semiconductor device. Ideally,these fine patterns on the reticle should correspond to the circuitdesign data that was used to generate the reticle (and possibly also thebaseline image. However, as the reticle patterns are being written ontothe reticle, misalignments may occur between two or more groups ofpatterns.

As shown, each columns of patterns is misaligned from the adjacentcolumn of patterns. For example, column 806 f is vertically misalignedfrom column 806 e. A magnified view 808 b is also illustrated forcolumns 806 f and 806 e. As shown, row 804 d of column 806 f ismisaligned from row 804 d of column 806 e by amount 810.

When the features of a test image that is generated from reticle 802 arecompared to features of a baseline image (e.g., in an edge to edgeanalysis), statistical information for any misalignment within thereticle may be collected and stored for later analysis. This statisticalinformation may be useful even when an error is not detected. Forexample, this misalignment information may indicate that the reticlewriter is becoming increasingly misaligned. Thus, statisticalinformation for misalignment for a group of reticles that were producedwith a same reticle writer may be collected and analyzed to determinedwhether the misalignment is increasing for each generated reticle.

The techniques of the present invention have several advantages. Forexample, since statistical information is collected and stored for oneor more characteristics of the reticle, the reticle may be globallyanalyzed in many useful applications. In a process monitoringapplication, the statistical information may allow process engineers tomore accurately monitor their semiconductor process. By way of aspecific example, it may be determined whether deviations betweenmeasurements of a particular characteristic on the wafer itself, such asline width, are a result of the reticle or of a particular process step.Additionally, the process may be adjusted for particular portions of thereticle to compensate for the reticle deviations. In sum, the presentinvention facilitates monitoring and fine tuning of the semiconductorprocess.

In a reticle generation application, the statistical information may beutilized to fine tune the reticle writing process. That is, theinformation may be analyzed to determine problem areas within thereticle writing process. The reticle writing process may then beadjusted for those particular problem areas. Additionally, thestatistical information may be utilized to increase the sensitivity of athreshold value that is used to inspect a particular problem region ofthe reticle. Also, statistical information may be collected for a samereticle process for several reticles and analyzed to determine if thereare any significant trends within the statistical information. Thesetrends may indicate that the reticle writing process, for example, isbeginning to vary towards unacceptable results. In other words, thestatistical information for a plurality of reticles may allow predictionof errors in the reticle generation process.

The invention may be used with any suitable inspection or fabricationsystem. FIG. 8 shows a reticle inspection system 900 where process 108of FIG. 1 of evaluating the reticle is implemented in one embodiment ofthe present invention. An autoloader 208 for automatically transportingreticles includes a robot 212 having an arm 210 extending towards ainspection port 202 of a reticle inspection station 250. Arm 210 mayrotate and extend towards an external port 204 when in its state denotedby reference number 210′. Similarly, when in its state denoted byreference number 210″, the robotic arm can also extend towards a storageport 206 of a reticle stocker station 216 that typically includesseveral slots or tracks for storing reticles. The robotic arm isdesigned to further extend and retrieve a reticle 214 from reticlestocker station 216.

A typical inspection process, according to one embodiment of the presentinvention, may begin after reticle 214 is placed on external port 204,with the intention of storing the reticle in reticle stocker station 216until it is used in a subsequent inspection application, for example.Robotic arm in its position 210′ transports the reticle from externalport 204 and stores it in a loading port of reticle stocker station 216by extending as shown in FIG. 8. When the reticle is needed forproduction, for example, robotic arm 210″ retrieves reticle 214 from theloading port and places it on inspection port 202 of reticle inspectionstation.

The reticle inspection station 250 is coupled with a computer system 252where evaluation process 108 of FIG. 1 detailed above is carried out andit is determined whether the reticle has passed inspection. The computersystem 252 may be integral to reticle inspection station 250 or separatefrom the inspection station 250. The reticle inspection station 250receives design data 254 in the form of a list of figures, for example.Additionally, the computer system 252 receives image data (i.e., a testimage) from the inspection station 250. The image data is analyzed bycomparing it to a baseline image, which may be generated from the designdata 254 or from the reticle 214. After the reticle inspection hasconcluded, reticle 214 is placed on external port 204 so that it may becarried to a fabrication facility for use, assuming of course, that ithas passed inspection. Alternatively, the reticle 214 may be repaired orremade.

Suitable computer systems for use in implementing and controlling themethods in the present invention (e.g., controlling the settings of thevarious scanning apparatus components, storing and retrieving a baselineimage of the reticle, storing a test image of the reticle, comparing thetest image with the baseline image, storing the defects and statisticalinformation during such comparisons, etc.) may be obtained from variousvendors (e.g., Silicon Graphics of Mountain View, Calif. or SunMircosystems of Sunnyvale, Calif.) or custom built by a reticleinspection system vendor, such as KLA-Tencor.

The term “electronic representation” as used herein covers any machinereadable representation. Typically, such representations are stored onmagnetic, electronic, or optically readable media. The content of suchrepresentations may be transmitted as electrical signals, magneticsignals, electromagnetic signals, optical signals, etc.

Preferably, an optical, electron beam, or other inspection system isintegrated with a computer system which implements many of the methodsteps of this invention. Such composite system preferably includes atleast (a) a baseline image (preferably compacted) stored in memory, (b)an imaging system arranged to generate an optical or electron beam imageof the reticle, and (c) a processing unit configured to compare thebaseline and current test images and thereby identify defects, as wellas compute and store various statistical information. At a minimum, theimaging system will usually include (i) a source of illuminationoriented to direct radiation onto a specified location of the reticle;and (ii) one or more detectors oriented to detect an image of thereticle from the source which has been scattered by the reticle. Theimaging system may also include a scanning means.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. It should be noted that there are many alternative waysof implementing both the process and apparatus of the present invention.For example, the collected statistical information may be utilized afterthe reticle is used to form patterns on a semiconductor wafer. That is,the statistical information may be used to correlate wafer statisticalinformation, and hence separate the new errors introduced during waferprocessing from the errors on the reticle. Accordingly, the presentembodiments are to be considered as illustrative and not restrictive,and the invention is not to be limited to the details given herein, butmay be modified within the scope and equivalents of the appended claims.

What is claimed is:
 1. A method of inspecting a sample, the methodcomprising: providing a test image of the sample, the test image havinga plurality of test features each having one or more measurable testcharacteristic values; providing a baseline image containing an expectedpattern of the test image, the baseline image having a plurality ofbaseline features each having one or more measurable baselinecharacteristic values, wherein each measurable baseline characteristicvalue is expected to match a corresponding one of the measurable testcharacteristic value; comparing at least a first subset and a secondsubset of the test characteristic values to their correspondingmeasurable baseline characteristic values such that a plurality ofdifference values are calculated for each pair of measurable test andbaseline characteristic values; and during the comparison, collectingstatistical information that is determined from at least a second subsetof the measurable test characteristic values or the difference valuesresulting from the comparison, wherein the statistical informationincludes a median or average value of the second subset of themeasurable test characteristic values.
 2. A method as recited in claim1, wherein the statistical information further includes the secondsubset of measurable test characteristic values and the second subsetdiffers from the first subset of measurable test characteristic valueswhich are compared to corresponding measurable test characteristicvalues.
 3. A method as recited in claim 2, wherein the statisticalinformation further includes a parameter selected from the groupconsisting of a standard deviation value of the second subset of themeasurable test characteristic values, a maximum value, a minimum value,and a range value of the second subset of the measurable testcharacteristic values.
 4. A method as recited in claim 2, wherein thefirst subset of measurable test characteristic values are in the form ofedge position values and the second subset of measurable testcharacteristic values are selected from the group consisting of linewidth values, corner rounding values, transmission values, gate linewidth values, contact area values, and misalignment values.
 5. A methodas recited in claim 2, wherein the statistical information furtherincludes the second subset of measurable test characteristic values as afunction of a predetermined parameter.
 6. A method as recited in claim5, wherein the predetermined parameter is a position on the sample.
 7. Amethod as recited in claim 5, wherein the predetermined parameter is afeature density value of an area on the sample.
 8. A method as recitedin claim 5, wherein the predetermined parameter is a semiconductorprocess associated with the sample, and the statistical informationfurther includes a standard deviation value of the second subset of themeasurable test characteristic values that is determined for a pluralityof samples associated with the semiconductor process.
 9. A method asrecited in claim 1, further comprising reporting an error for a selectedone of the measurable test characteristic values if the selectedmeasurable test characteristic value and the corresponding baselinecharacteristic value have an associated difference value that is morethan a predetermined threshold.
 10. A method as recited in claim 1,wherein the statistical information further includes a parameterselected from the group consisting of a maximum value, a minimum value,and a range value of the second subset of the measurable testcharacteristic values.
 11. A method as recited in claim 10, wherein theaverage, maximum, minimum, range, median, and standard deviation valuesare correlated with a particular region of the sample.
 12. A method asrecited in claim 11, wherein the average, maximum, minimum, range,median, and standard deviation values are further correlated with afeature density value of the particular region of the sample.
 13. Amethod as recited in claim 10, wherein the average, maximum, minimum,range, median, and standard deviation values are correlated with aparticular process associated with the sample.
 14. A method as recitedin claim 1, wherein the statistical information further includes a countof at least the second subset the measurable test characteristic values.15. A method as recited in claim 10, wherein the measurable testcharacteristic values are selected from the group consisting of linewidth values, corner rounding values, transmission values, gate linewidth values, contact area values, and misalignment values.
 16. A methodas recited in claim 1, wherein the statistical information furtherincludes the second subset of the measurable test characteristic valuesas a function of a predetermined parameter.
 17. A method as recited inclaim 16, wherein the predetermined parameter is a position on thesample.
 18. A method as recited in claim 16, wherein the predeterminedparameter is a feature density value of an area on the sample.
 19. Amethod as recited in claim 16, wherein the predetermined parameter is asemiconductor process associated with the sample, and the statisticalinformation is collected for a plurality of samples associated with theprocess.
 20. A method as recited in claim 9, wherein the statisticalinformation further includes a parameter selected from the groupconsisting of a standard deviation value, a maximum value, a minimumvalue, a range value, and a median or average value of the differencevalues.
 21. A method as recited in claim 9, wherein the statisticalinformation further includes a count of the difference values, astandard deviation value of such difference values and a median oraverage value of the difference values.
 22. A method as recited in claim20, wherein the measurable test characteristic values are selected fromthe group consisting of line width values, corner rounding values,transmission values, gate line width values, contact area values, andmisalignment values.
 23. A method as recited in claim 9, wherein thestatistical information further includes the difference values as afunction of a predetermined parameter.
 24. A method as recited in claim23, wherein the predetermined parameter is a position on the sample. 25.A method as recited in claim 23, wherein the predetermined parameter isa feature density value of an area on the sample.
 26. A method asrecited in claim 23 wherein the predetermined parameter is the sample'scorresponding semiconductor process, and the statistical information iscollected for a plurality of samples corresponding to the semiconductorprocess.
 27. A method as recited in claim 1, wherein the measurable testcharacteristic values are selected from the group consisting of linewidth values, corner rounding values, transmission values, gate linewidth values, contact area values, and misalignment values.
 28. A methodas recited in claim 9, further comprising adjusting the predeterminedthreshold for portions of the test image based on the collectedstatistical information.
 29. A method as recited in claim 1, wherein thesample is a semiconductor wafer or device.
 30. A method as recited inclaim 1, wherein the sample is a reticle.
 31. A computer readable mediumcontaining program instructions for inspecting a sample, the computerreadable medium comprising: computer readable code for providing a testimage of the sample, the test image having a plurality of test featureseach having one or more measurable test characteristic values; computerreadable code for providing a baseline image containing an expectedpattern of the test image, the baseline image having a plurality ofbaseline features each having one or more measurable baselinecharacteristic values, wherein each measurable baseline characteristicvalue is expected to match a corresponding one of the measurable testcharacteristic value; computer readable code for comparing at least afirst subset and a second subset of the test characteristic values totheir corresponding measurable baseline characteristic values such thata plurality of difference values are calculated for each pair ofmeasurable test and baseline characteristic values; computer readablecode for during the comparison, collecting statistical information thatis determined from at least a second subset of the measurable testcharacteristic values or the difference values resulting from thecomparison, wherein the statistical information includes a standarddeviation value of the second subset of the measurable testcharacteristic values and a median or average value of the second subsetof the measurable test characteristic values as a function of apredetermined parameter; and a computer readable medium for storing thecomputer readable codes.